The 3D structure of SARS-CoV-2 targets (surface glycoproteins (6VSB; 6M0J), RNA dependent RNA polymerase (6M71) and main protease (6Y84)) were downloaded as PDB files from the protein data bank (https://www.rcsb.org/) and were optimized for molecular docking in the Chimera software.[19]
The structures of selected natural compounds in Tinospora cordifolia (Berberine, Tinocordiside, CordifolisideA, Jatrorrhizine, Magnoflorine, Isocolumbin, Sinapic acid, Syringin and Palmatine) were accessed from PubChem database and processed into PDB file format and minimised for molecular docking using the Chimera software.[19, 20] Molecular docking was performed to evaluate the binding efficacy of these compounds against the SARS-CoV-2 targets using AutoDock Vina (version 1.5.4) and the docked protein-ligand complex were visualised using the Chimera and PyMOL v 1.8.2.0 software[19-22]. AutoDock-MGLTools was employed to visualize and modify the receptor and ligand structures to PDBQT file formats. The PDBQT file formats of the ligand and receptor were used for molecular docking using the AutoDock Vina program. Ligands were docked individually to the receptor with grid coordinates and grid boxes of specific sizes for each receptor centralised in the AutoDock-MGLTools. The output file was saved in the PDBQT format and the ligand-receptor binding affinity estimated as negative Gibbs free energy (∆G) scores (Kcal/mol), were documented based on AutoDock Vina scoring function. Post-docking analyses were visualized using PyMOL and Chimera, giving details of the sizes, locations of binding sites, hydrogen-bond interactions of the docked ligand in various confirmations.
Simulation of dose response curves: Dose-response curves were modelled based on nonlinear regression analysis approach by specifying IC50 values as independent variable and response (% inhibition) as dependent variable. IC50 values were estimated from the binding affinity values using the following formula IC50 = exp(deltaG/RT) (1+ ([S]/Km)). Where deltaG = Binding affinity (Kcal/mol), RT = 298K, S = substrate concentration, Km=Michaelis constant. The increase in the ligand dose increases results in sequential changes to the response (% receptor inhibition) eventually achieving minimum or maximum response limits. As the 20 to 80% response is linear, this was modelled using four-point logistic increments of IC50 values (0.5x, 1x, 1.5x and 2x) and averaged. The resulting equation from this was y = 26.362x - 158.85 (R² = 0.9967). This one standard deviation increase and decrease of the IC50 values was estimated from this equation. The resulted three IC50 values estimated were used to calculate the IC 5, 20, 60, 80 and 100 values by employing a five-parameter logistic equation[23]. The means of the IC 5, 20, 60, 80 and 100 values obtained (in x axis) were plotted against the % inhibition response (in y axis) to obtain the simulated dose response curves.